Bio-inspired Cognitive Architecture for Adaptive Agents based on an Evolutionary Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Oscar Romero and Angelica {de Antonio}",
  title =        "Bio-inspired Cognitive Architecture for Adaptive
                 Agents based on an Evolutionary Approach",
  year =         "2008",
  booktitle =    "Adaptive Learning Agents and Multi-Agent Systems
                 Workshop at AAMAS 2008",
  editor =       "Franziska Kluegl and Sandip Sen and Karl Tuyls",
  address =      "Estoril, Portugal",
  month =        "12 " # may,
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming",
  URL =          "",
  size =         "8 pages",
  abstract =     "In this work, an hybrid, self-configurable,
                 multilayered and evolutionary subsumption architecture
                 for cognitive agents is developed. Each layer of the
                 multilayered architecture is modelled by one different
                 Reinforcement Machine Learning System (RMLS) based on
                 bio-inspired techniques. In this research an
                 evolutionary mechanism based on Gene Expression
                 Programming to self-configure the behaviour arbitration
                 between layers is suggested. In addition, a
                 co-evolutionary mechanism to evolve behaviours in an
                 independent and parallel fashion is used too. The
                 proposed approach was tested in an animat environment
                 (artificial life) using a multi-agent platform and it
                 exhibited several learning capabilities and emergent
                 properties for self-configuring internal agent's
  notes =        "pages


        held in cooperation
                 with AAAI.",

Genetic Programming entries for Oscar Javier Romero Lopez Angelica de Antonio Jimenez